The security of computing resources and associated data is of high importance in many contexts. As an example, organizations often utilize networks of computing devices to provide a robust set of services to their users. Networks often span multiple geographic boundaries and often connect with other networks. An organization, for example, may support its operations using both internal networks of computing resources and computing resources managed by others connected through external networks. Computers of the organization, for instance, may communicate with computers of other organizations to access and/or provide data while using services of another organization. In many instances, organizations configure and operate remote networks using hardware managed by other organizations, thereby reducing infrastructure costs and achieving other advantages. With such configurations of computing resources, ensuring that access to the resources and the data they hold is secure can be challenging, especially as the size and complexity of such configurations grow.
Modern cryptographic algorithms provide high levels of data security. Current encryption methods, for example, can secure data such that unauthorized access to the data requires an impractical amount of time and/or resources. Such high-levels of protection, however, come at a cost. Generally speaking, higher levels of protection require higher levels of care and greater expenditure of computational resources. At the same time, it may be inefficient and/or impractical to employ such high levels of data security at certain levels or at a certain scale. As an example, data and files stored in a file system may be encrypted; however, rotating and other protections of the encryption key and data may be impractical due to the large amount of computational resources required. Generally, a lot of computational resources are required to effectively protect data within a file system, resulting in decreased security, over utilization of computational resources, and exposure of sensitive data, among other issues.